Intelligent Task Scheduling in Multi UAVs During the Flood Relief Operation

An increasing interest in the design of Unmanned Systems (US) in firefighting, surveillance, delivering some living supplies, mapping for disaster recovery, and search and rescue (SAR) missions. However, only a limited number of studies have been reported on US scheduling in a 3D environment. Dynamic task scheduling plays a very critical role in coping with emergent tasks. In this paper, we investigate a multi-autonomous system collaborating unmanned aerial vehicles (UAV) and unmanned surface vehicles (USV) systems to execute various tasks in SAR operations in flood-isolated areas. A search technique has to be carried out to scan the damaged region, the number of UAVs to be used for a particular SAR operation, speeding up the searching process, and find any probable survivors, sending USV to rescue the survivors. The autopilot is present in the UAVs are optimized with a controller, which monitors the reference path while maximizing flight duration, while optimization of flight paths may include other features, such as the determination of arrival time at each point, utilization of UAVs, battery capacity considerations, and battery recharging considerations. Task scheduling is a significant difficulty for researchers and practitioners involved in multi-UAV operations. Here, we propose a conceptual model of a scheduling system for UAV and USV deployments and specify dependencies between them.